{"title":"MRI Evaluation of Indeterminate Pulmonary Nodules.","authors":"Mark M Hammer, Rachna Madan","doi":"10.1097/RCT.0000000000001844","DOIUrl":null,"url":null,"abstract":"<p><strong>Purpose: </strong>To evaluate MRI features for differentiating pulmonary hamartomas from other nodule pathologies, including carcinoid tumors and non-small cell lung cancer (NSCLC).</p><p><strong>Materials and methods: </strong>This retrospective study analyzed chest MRIs of 48 patients with pulmonary nodules from 2017 to 2025. Patients had either pathologic diagnosis or stable follow-up confirming hamartoma. Two blinded radiologists reviewed images and recorded enhancement pattern (solid, rim, or speckled/mesh). The signal intensity index (SII) was calculated using chemical shift imaging.</p><p><strong>Results: </strong>Hamartomas (n=19, 40%), carcinoids (n=17, 35%), and adenocarcinomas (n=9, 19%) were the most common diagnoses. Rim and speckled/mesh enhancement patterns were nearly exclusive to hamartomas (22% and 39% vs. 0% and 4%, respectively, P <0.001). An SII >10% showed 61% sensitivity and 100% specificity for hamartomas. Combining rim or speckled/mesh enhancement patterns and SII >10% yielded 79% sensitivity and 96.6% specificity for hamartomas.</p><p><strong>Conclusions: </strong>Although chemical shift imaging is diagnostic for hamartomas, signal dropout is present in just over half of cases. Rim or speckled/mesh enhancement patterns are also highly suggestive. Combining these MRI features significantly improves diagnostic accuracy for pulmonary hamartomas, potentially reducing further follow-up or invasive procedures for indeterminate nodules.</p>","PeriodicalId":15402,"journal":{"name":"Journal of Computer Assisted Tomography","volume":" ","pages":"650-655"},"PeriodicalIF":1.4000,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Computer Assisted Tomography","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1097/RCT.0000000000001844","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/12/15 0:00:00","PubModel":"Epub","JCR":"Q4","JCRName":"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING","Score":null,"Total":0}
引用次数: 0
Abstract
Purpose: To evaluate MRI features for differentiating pulmonary hamartomas from other nodule pathologies, including carcinoid tumors and non-small cell lung cancer (NSCLC).
Materials and methods: This retrospective study analyzed chest MRIs of 48 patients with pulmonary nodules from 2017 to 2025. Patients had either pathologic diagnosis or stable follow-up confirming hamartoma. Two blinded radiologists reviewed images and recorded enhancement pattern (solid, rim, or speckled/mesh). The signal intensity index (SII) was calculated using chemical shift imaging.
Results: Hamartomas (n=19, 40%), carcinoids (n=17, 35%), and adenocarcinomas (n=9, 19%) were the most common diagnoses. Rim and speckled/mesh enhancement patterns were nearly exclusive to hamartomas (22% and 39% vs. 0% and 4%, respectively, P <0.001). An SII >10% showed 61% sensitivity and 100% specificity for hamartomas. Combining rim or speckled/mesh enhancement patterns and SII >10% yielded 79% sensitivity and 96.6% specificity for hamartomas.
Conclusions: Although chemical shift imaging is diagnostic for hamartomas, signal dropout is present in just over half of cases. Rim or speckled/mesh enhancement patterns are also highly suggestive. Combining these MRI features significantly improves diagnostic accuracy for pulmonary hamartomas, potentially reducing further follow-up or invasive procedures for indeterminate nodules.
期刊介绍:
The mission of Journal of Computer Assisted Tomography is to showcase the latest clinical and research developments in CT, MR, and closely related diagnostic techniques. We encourage submission of both original research and review articles that have immediate or promissory clinical applications. Topics of special interest include: 1) functional MR and CT of the brain and body; 2) advanced/innovative MRI techniques (diffusion, perfusion, rapid scanning); and 3) advanced/innovative CT techniques (perfusion, multi-energy, dose-reduction, and processing).